Remote Data Scientist — Retail AI & Forecasts (Mexico)

7Learnings; Xico; Remote; MXN 600,000 - 1,200,000; Full time

Benefits offered by this job

Flexible hours

Remote from Mexico

30 vacation days

Culture of trust

Personal responsibility

Job summary

7Learnings is seeking an autonomous Data Scientist based in Mexico to own the intersection of predictive decision-making and robust software engineering for our North American operations. Working remotely from Mexico, you will support our US clients with ML-driven insights and scalable solutions.

You will collaborate with our Berlin-based engineering team to translate retail challenges into production-ready models and data pipelines, ensuring high accuracy and low technical debt while aligning

Qualifications

• Bachelor’s or Master’s degree in quantitative fields such as CS, math, physics, or similar.
• Hands-on experience in machine learning and data science.
• Strong English proficiency (C1–C2) and excellent communication.
• Located in Mexico and aligned with US time zones.

Responsibilities

• Leverage analytical skills to support US retail optimization projects.
• Experiment with ML models to forecast sales and costs.
• Interface with retailers to continuously improve the 7Learnings software.
• Collaborate closely with our global engineering team.
• Optimize our data pipelines and predictive model codebases.
• Support the monitoring, measurement, and exploration of large-scale datasets.

Skills

Machine learning

Data science

Communication

Stakeholder management

English proficiency

Education

Bachelor’s or Master’s degree in quantitative fields

Tools

Git

TensorFlow

Google Cloud Platform

SQL

BigQuery

Job description

7Learnings is seeking an autonomous Data Scientist based in Mexico to own the intersection of predictive decision-making and robust software engineering for our North American operations. Working remotely from Mexico, you will support our US clients with ML-driven insights and scalable solutions.

You will collaborate with our Berlin-based engineering team to translate retail challenges into production-ready models and data pipelines, ensuring high accuracy and low technical debt while aligning